With the aid of modern imaging methods, two or three-dimensional image data is often created that can be used for visualizing an imaged examination object and also for further uses.
Frequently, the imaging methods are based on the detection of X-ray radiation, wherein “projection scan data” is generated. For example, projection scan data can be acquired with the aid of a computed tomography (CT) system. In CT systems, typically, a combination of an X-ray source and an oppositely arranged X-ray detector mounted on a gantry runs around a measurement space in which the examination object (which in the following is designated “patient” without any restriction of the generality) is situated. The center of rotation (also known as “isocenter”) coincides with a “system axis” z. During one or two rotations, the patient is irradiated with X-ray radiation from the X-ray source, wherein projection scan data or X-ray projection data is acquired with the aid of the X-ray detector positioned opposite thereto.
The projection scan data, or “projection data” for short, is dependent, in particular, on the construction of the X-ray detector. X-ray detectors typically have a plurality of detector units that are usually arranged in a regular pixel array. The detector units each generate, for X-ray radiation falling on the detector units, a detector signal that is analyzed at particular time points with regard to intensity and spectral distribution of the X-ray radiation in order to draw conclusions about the examination object and to generate projection scan data.
Conventionally, CT image data has image points with gray scale values that correspond to the measured attenuation value at each individual image point of a region to be imaged. Where reference is made below to an image point, this is intended to mean, for example, a two-dimensional pixel or a three-dimensional voxel. The measured attenuation value is the value that the relevant object point in the region to be imaged contributes to the overall attenuation that the incident X-ray radiation has experienced. This attenuation value is given in Hounsfield units. Herein, a value of −1000 HU corresponds to an attenuation that is produced by air and 0 HU to an attenuation that matches the attenuation of water. Conventionally, the image data is represented as gray scale-encoded two-dimensional images.
In order to take account of the third dimension of a volume region to be imaged, various representational possibilities exist. For example, a plurality of two-dimensional images are represented adjoining one another. Herein, each of the two-dimensional images represents a slice of a three-dimensional volume. The two-dimensional images can also be depicted one after another, so that the volume imaged can be leafed through with a mouse or another controlling input device. In order to form the individual slice images, for example, three-dimensional image data material that is assigned to a slice can be reformatted. Herein, for example, averaging of the image data in the slice direction, i.e. in the direction perpendicular to the slice plane, is carried out and the calculated average is represented in a two-dimensional image assigned to the slice. Reformatting of this type is known as multi-planar reformatting (MPR). Alternatively, a calculation of the maximum or minimum value in the direction perpendicular to the slice plane can be carried out and the calculated maximum or minimum value can be represented in a two-dimensional image assigned to the slice. In the case of a representation of the maximum values, a procedure of this type can be referred to as a projection of the maximum intensity value (maximum intensity projection, MIP). In the case of a representation of the minimum values, a procedure of this type can be referred to as a projection of the minimum intensity value (minimum intensity projection, MinIP).
In a series of uses of CT systems, a plurality of data sets or projection data sets that relate to the same object are acquired from independent scans. Data sets of this type are recorded, for example, for the use of recordings with a plurality of energy thresholds, known as multi-energy scans. In the multi-energy scans, data of a quantum-counting detector is acquired with one or more energy thresholds, wherein different data sets are assigned to the respective energy ranges separate from the energy thresholds.
In this case, for each point of a region to be imaged, a plurality of attenuation values exist that are each assigned to one of the different data sets and, taken together, describe the spectral dependency of the attenuation values of the incident X-ray radiation. In principle, spectral dependencies can be characterized by the specification of different attenuation values for different spectra or spectral intervals or by the specification of the portions of different base materials at the respective measuring point. Herein, partial spectra, which together form the overall spectrum of the spectral dependency of the image data, are assigned to the base materials. The spectral dependency of the image data therefore corresponds to a fourth dimension in the data generated during the scan. Four-dimensional scan data can only be represented graphically with difficulty.
Conventionally, this four-dimensional data is divided into three-dimensional volume data that corresponds, respectively, to a spectral portion. The three-dimensional data separated according to spectral portion is separately displayed. However, a representation of this type of four-dimensional scan data is very unclear and complex.